Cloud energy storage full-amount battery cell internal resistance calculation and evaluation method

Abstract

The invention discloses a cloud energy storage full-amount battery cell internal resistance calculation and evaluation method, which comprises the following steps: acquiring battery cell-level full-amount data, and dividing and storing the acquired battery cell-level full-amount data; inputting the stored cell-level total data into a preset evaluation model to obtain a cell internal resistance database; establishing a cell internal resistance data matrix through the cell internal resistance database, and calculating a feature vector of the cell internal resistance data matrix; and analyzing the correlation between the feature vectors to evaluate the state of the battery. According to the method, historical operation data of a big data platform is utilized, the internal resistance change of the battery cell is calculated based on a data driving mode by fitting the equivalent mathematical model of the battery cell, and the method has the advantages of full coverage and high fitting precision; the problems that only cluster is involved in the traditional method, the internal resistance calculation of the Pack level is inaccurate, and the full quantity of battery cells in the cluster cannot be calculated and evaluated are solved.

Description

technical field [0001] The invention relates to the field of battery management, in particular to a method for calculating and evaluating the internal resistance of a full-capacity cell of cloud energy storage. Background technique [0002] With the advancement of energy storage technology, more and more energy storage systems are connected to the power grid, providing flexible and dispatchable energy reserves for building a strong grid and smart grid. For the operation and maintenance of the centralized and distributed energy storage system, the safe operation of the battery is the primary consideration. The battery is mainly composed of cells and protective plates that protect the cells. [0003] Between different energy storage systems, there are inevitably differences in the grouping, structure, assembly, and environment of battery clusters and packs, which will affect the operating characteristics of the system. At the same time, due to the highly nonlinear and degrada...

AI Technical Summary

Problems solved by technology

[0007] Insufficient AC measurement: the line is susceptible to external interference, and the accuracy is not as high as the DC measurement method

[0008] DC measurement is generally used in the test of large-capacity batteries (large-capacity lead-acid batteries, or lithium batteries). The disadvantages of this method: 1. It needs to generate a large current, otherwise the voltage difference and current difference will change very little. The calculation of this small difference will amplify the acquisition and calculation errors; 2. The BMS working cycle is very short, the response speed of the voltage sensor and the current sensor may be inconsistent, and the delay in the response of the voltage to the current, etc., will lead to the calculation of the internal resistance. 3. There is a deviation in a single calculation, and the obtained internal resistance is very unstable, which violates the principle of gradual change of internal resistance, and multiple tests are required; 4. Online detection cannot be performed during the normal operation of the system, and HPPC (mixed Pulse) pulse charge and discharge to detect, it is not convenient for the continuous operation of the system

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